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Opportunities and Challenges from Using Animal Videos in Reinforcement Learning for Navigation

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arXiv 2022年

作者： Giammarino, Vittorio Queeney, James Carstensen, Lucas C. Hasselmo, Michael E. Paschalidis, Ioannis Ch. Division of Systems Engineering Boston University BostonMA02215 United States Center for Systems Neuroscience Department of Psychological and Brain Sciences Graduate Program for Neuroscience Boston University BostonMA02215 United States College of Engineering Hariri Institute for Computing & Computational Science & Engineering Boston University BostonMA02215 United States

We investigate the use of animal videos (observations) to improve Reinforcement Learning (RL) efficiency and performance in navigation tasks with sparse rewards. Motivated by theoretical considerations, we make use of weighted policy optimization for off-policy RL and describe the main challenges when learning from animal videos. We propose solutions and test our ideas on a series of 2D navigation tasks. We show how our methods can leverage animal videos to improve performance over RL algorithms that do not leverage such observations. © 2022, CC BY.

关键词： Reinforcement learning

Towards Fabrication of Next-Generation Physical Sensors Through Integrating Suspended Sub-Micron Silicon Nanowires with Microelectromechanical Systems

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Towards Fabrication of Next-Generation Physical Sensors Thro...

IEEE SENSORS

作者： Basit Ali Mehdi Bostan Shirin Muhammad Muzammil Ege Nacarkucuk Sina Zare Pakzad Umut Kerimzade B. Erdem Alaca Department of Mechanical Engineering Koç University Istanbul Turkey Computational Sciences and Engineering Program Koç University Istanbul Turkey Institute of Sensor and Actuator Systems TU Wien Austria Christian Doppler Laboratory for Piezoelectric Silicon MEMS with Enhanced Sensitivity and Responsivity Institute of Sensor and Actuator Systems TU Wien Austria nSTAR-Koç University Nanofabrication and Nanocharacterization Center for Scientific and Technological Advanced Research Koç University Istanbul Turkey Surface Science and Technology Center (KUYTAM) Koç University Istanbul Turkey

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

Silicon nanowires possess superior mechanical, electrical, and optical properties, making them ideal for next-generation sensors. This study presents a scalable technology for monolithic fabrication of sub-micron silicon nanowires with micro electromechanical systems, achieving integration of suspended sub-micron silicon nanowires within microelectromechanical systems up to 80 μm thick on Si substrates, with high yield and repeatability. The technological approach is validated on silicon-on-insulator substrates, followed by electromechanical characterization via electrical probe measurements and vibrational testing for performance validation. The presented technology is promising for the potential development of next-generation high-performance physical sensors such as accelerometers and gyroscopes.

关键词： Microelectromechanical systems Sensor phenomena and characterization Vibration measurement Silicon Sensor systems Nanowires Optical sensors Next generation networking Substrates Electromechanical sensors

On Time Uniform Wong-Zakai Approximation Theorems

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arXiv 2023年

作者： Del Moral, Pierre Hu, Shulan Jasra, Ajay Ruzayqat, Hamza Wang, Xinyu Institut de Mathematiques de Bordeaux Bordeaux33405 France School of Statistics and Mathematics Zhongnan University of Economics and Law China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Wenlan School of Business Zhongnan University of Economics and Law China

We consider the long time behavior of Wong-Zakai approximations of stochastic differential equations. These piecewise smooth diffusion approximations are of great importance in many areas, such as those with ordinary differential equations associated to random smooth fluctuations;e.g. robust filtering problems. In many examples, the mean error estimate bounds that have been derived in the literature can grow exponentially with respect to the time horizon. We show in a simple example that indeed mean error estimates do explode exponentially in the time parameter, i.e. in that case a Wong-Zakai approximation is only useful for extremely short time intervals. Under spectral conditions, we present some quantitative time-uniform convergence theorems, i.e. time-uniform mean error bounds, yielding what seems to be the first results of this type for Wong-Zakai diffusion *** Codes 60H35(Primary), 65C30(Secondary) Copyright © 2023, The Authors. All rights reserved.

关键词： Brownian movement

On the Particle Approximation of Lagged Feynman-Kac Formulae

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arXiv 2024年

作者： Awadelkarim, Elsiddig Caffarel, Michel Moral, Pierre Del Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia University of Toulouse CNRS-Lab. de Chimie et Physique Quantiques Toulouse31062 France Centre de Recherche Inria Bordeaux Sud-Ouest Talence33405 France School of Data Science The Chinese University Hong Kong Shenzhen China

In this paper we examine the numerical approximation of the limiting invariant measure associated with Feynman-Kac formulae. These are expressed in a discrete time formulation and are associated with a Markov chain and a potential function. The typical application considered here is the computation of eigenvalues associated with non-negative operators as found, for example, in physics or particle simulation of rare-events. We focus on a novel lagged approximation of this invariant measure, based upon the introduction of a ratio of time-averaged Feynman-Kac marginals associated with a positive operator iterated l ∈ N times;a lagged Feynman-Kac formula. This estimator and its approximation using Diffusion Monte Carlo (DMC) have been extensively employed in the physics literature. In short, DMC is an iterative algorithm involving N ∈ N particles or walkers simulated in parallel, that undergo sampling and resampling operations. In this work, it is shown that for the DMC approximation of the lagged Feynman-Kac formula, one has an almost sure characterization of the L1-error as the time parameter (iteration) goes to infinity and this is at most of O(exp{−κl}/N), for_ κ > 0. In addition a non-asymptotic in time, and time uniform L1−bound is proved which is O(l/√N). We also prove a novel central limit theorem to give a characterization of the exact asymptotic in time variance. This analysis demonstrates that the strategy used in physics, namely, to run DMC with N and l small and, for long time enough, is mathematically justified. Our results also suggest how one should choose N and l in practice. We emphasize that these results are not restricted to physical applications;they have broad relevance to the general problem of particle simulation of the Feynman-Kac formula, which is utilized in a great variety of scientific and engineering fields. © 2024, CC BY.

关键词： Eigenvalues and eigenfunctions

Multi-index Sequential Monte Carlo ratio estimators for Bayesian Inverse problems

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arXiv 2022年

作者： Law, Kody J.H. Walton, Neil Yang, Shangda Jasra, Ajay School of Mathematics University of Manchester ManchesterM13 9PL United Kingdom Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

We consider the problem of estimating expectations with respect to a target distribution with an unknown normalizing constant, and where even the unnormalized target needs to be approximated at finite resolution. This setting is ubiquitous across science and engineering applications, for example in the context of Bayesian inference where a physics-based model governed by an intractable partial differential equation (PDE) appears in the likelihood. A multi-index Sequential Monte Carlo (MISMC) method is used to construct ratio estimators which provably enjoy the complexity improvements of multi-index Monte Carlo (MIMC) as well as the efficiency of Sequential Monte Carlo (SMC) for inference. In particular, the proposed method provably achieves the canonical complexity of MSE−1, while single level methods require MSE−ξ for ξ > 1. This is illustrated on examples of Bayesian inverse problems with an elliptic PDE forward model in 1 and 2 spatial dimensions, where ξ = 5/4 and ξ = 3/2, respectively. It is also illustrated on more challenging log Gaussian process models, where single level complexity is approximately ξ = 9/4 and multilevel Monte Carlo (or MIMC with an inappropriate index set) gives ξ = 5/4 + ω, for any ω > 0, whereas our method is again canonical. We also provide novel theoretical verification of the product-form convergence results which MIMC requires for Gaussian processes built in spaces of mixed regularity defined in the spectral domain, which facilitates acceleration with fast Fourier transform methods via a cumulant embedding strategy, and may be of independent interest in the context of spatial statistics and machine learning. Copyright © 2022, The Authors. All rights reserved.

关键词： Inverse problems

Global dispersal and adaptive evolution of domestic cattle:a genomic perspective

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Stress Biology 2023年第1期3卷 98-110页

作者： Xiaoting Xia Kaixing Qu Yan Wang Mikkel-Holger SSinding Fuwen Wang Quratulain Hanif Zulfiqar Ahmed Johannes A.Lenstra Jianlin Han Chuzhao Lei Ningbo Chen Key Laboratory of Animal Genetics Breeding and Reproduction of Shaanxi ProvinceCollege of Animal Science and TechnologyNorthwest A&F UniversityYangling 712100China Academy of Science and Technology Chuxiong Normal UniversityChuxiong 675000China Qingdao Municipal Bureau of Agriculture and Rural Affairs Qingdao 266000China Section for Computational and RNA Biology Department of BiologyUniversity of CopenhagenCopenhagen 1350Denmark National Institute for Biotechnology and Genetic Engineering FaisalabadPakistan Faculty of Veterinary and Animal Sciences University of Poonch RawalakotAzad Jammu and Kashmir 12350Pakistan Faculty of Veterinary Medicine Utrecht UniversityUtrechtThe Netherlands Livestock Genetic Program International Livestock Research Institute(ILRI)Nairobi 00100Kenya CAAS-ILRI Joint Laboratory On Livestock and Forage Genetic Resources Institute of Animal ScienceChinese Academy of Agricultural Sciences(CAAS)Beijing 100193China

Domestic cattle have spread across the globe and inhabit variable and unpredictable *** have been exposed to a plethora of selective pressures and have adapted to a variety of local ecological and management conditions,including UV exposure,diseases,and stall-feeding *** selective pressures have resulted in unique and important phenotypic and genetic differences among modern cattle breeds/*** efforts to sequence the genomes of local and commercial cattle breeds/populations,along with the growing availability of ancient bovid DNA data,have significantly advanced our understanding of the genomic architecture,recent evolution of complex traits,common diseases,and local adaptation in ***,we review the origin and spread of domestic cattle and illustrate the environmental adaptations of local cattle breeds/populations.

关键词： Cattle Origin Domestication Migration route Environmental adaptation Selective pressure

CAFA-evaluator: A Python Tool for Benchmarking Ontological Classification Methods

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arXiv 2023年

作者： Piovesan, Damiano Zago, Davide Joshi, Parnal Clara De Paolis Kaluza, M. Mehdiabadi, Mahta Ramola, Rashika Monzon, Alexander Miguel Reade, Walter Friedberg, Iddo Radivojac, Predrag Tosatto, Silvio C.E. Department of Biomedical Sciences University of Padova Padova35121 Italy Program in Bioinformatics and Computational Biology Iowa State University AmesIA50011 United States Department of Veterinary Microbiology and Preventive Medicine Iowa State University AmesIA50011 United States Khoury College of Computer Sciences Northeastern University BostonMA02115 United States Department of Information Engineering University of Padova Padova35121 Italy Kaggle San FranciscoCA United States

We present CAFA-evaluator, a powerful Python program designed to evaluate the performance of prediction methods on targets with hierarchical concept dependencies. It generalizes multi-label evaluation to modern ontologies where the prediction targets are drawn from a directed acyclic graph and achieves high efficiency by leveraging matrix computation and topological sorting. The program requirements include a small number of standard Python libraries, making CAFA-evaluator easy to maintain. The code replicates the Critical Assessment of protein Function Annotation (CAFA) benchmarking, which evaluates predictions of the consistent subgraphs in Gene Ontology. Owing to its reliability and accuracy, the organizers have selected CAFA-evaluator as the official CAFA evaluation software. © 2023, CC BY.

关键词： Python

MultiCalib4DEB: A toolbox exploiting multimodal optimisation in Dynamic Energy Budget parameters calibration

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arXiv 2023年

作者： Robles, Juan Francisco Chica, Manuel Filgueira, Ramón Agüera, Antonio Damas, Sergio Department of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence DaSCI University of Granada Granada18071 Spain Department of Benthic resources Norwegian Institute of Marine Research BergenNO-5817 Norway Department of Software Engineering Andalusian Research Institute in Data Science and Computational Intelligence DaSCI University of Granada Granada18071 Spain Marine Affairs Program Life Sciences Centre Dalhousie University 1459 Oxford Street HalifaxNSB3H 4R2 Canada

1. Calibration is a crucial step for the validation of computational models and a challenging task to accomplish. 2. Dynamic Energy Budget (DEB) theory has experienced an exponential rise in the number of published papers, which in large part has been made possible by the DEBtool toolbox. Multimodal evolutionary optimisation could provide DEBtool with new capabilities, particularly relevant on the provisioning of equally optimal and diverse solutions. 3. In this paper we present MultiCalib4DEB, a MATLAB toolbox directly integrated into the existing DEBtool toolbox, which uses multimodal evolutionary optimisation algorithms to find multiple global and local optimal and diverse calibration solutions for DEB models. 4. MultiCalib4DEB adds powerful calibration mechanisms, statistical analysis, and visualisation methods to the DEBtool toolbox and provides a wide range of outputs, different calibration alternatives, and specific tools to strengthen the DEBtool calibration module and to aid DEBtool users to evaluate the performance of the calibration results. © 2023, CC BY-NC-ND.

关键词： Calibration

CONVERGENCE SPEED AND APPROXIMATION ACCURACY OF NUMERICAL MCMC

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arXiv 2022年

作者： Cui, Tiangang Dong, Jing Jasra, Ajay Tong, Xin T. School of Mathematics Monash University Australia Graduate School of Business Columbia University United States Applied Mathematics and Computational Science Program Computer Electrical Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Saudi Arabia Department of Mathematics National University of Singapore Singapore

When implementing Markov Chain Monte Carlo (MCMC) algorithms, perturbation caused by numerical errors is sometimes inevitable. This paper studies how perturbation of MCMC affects the convergence speed and Monte Carlo estimation accuracy. Our results show that when the original Markov chain converges to stationarity fast enough and the perturbed transition kernel is a good approximation to the original transition kernel, the corresponding perturbed sampler has similar convergence speed and high approximation accuracy as well. We discuss two different analysis frameworks: ergodicity and spectral gap, both are widely used in the literature. Our results can be easily extended to obtain non-asymptotic error bounds for MCMC estimators. We also demonstrate how to apply our convergence and approximation results to the analysis of specific sampling algorithms, including Random walk Metropolis and Metropolis adjusted Langevin algorithm with perturbed target densities, and parallel tempering Monte Carlo with perturbed densities. Finally we present some simple numerical examples to verify our theoretical claims. Copyright © 2022, The Authors. All rights reserved.

关键词： Inverse problems